Database Administrator

Database Administration and SQL
• Advanced SQL: Strong hands-on expertise in writing, reviewing and optimising complex SQL queries, joins, subqueries, views, stored procedures, functions and triggers.
• Query performance: Ability to analyse execution plans, identify


Database Administration and SQL
• Advanced SQL: Strong hands-on expertise in writing, reviewing and optimising complex SQL queries, joins, subqueries, views, stored procedures, functions and triggers.
• Query performance: Ability to analyse execution plans, identify bottlenecks, optimise indexes and queries, and resolve locking, blocking and long-running transaction issues.
• PostgreSQL administration: Proven experience installing, configuring, upgrading, patching and administering PostgreSQL databases across development, test and production environments.
• Database operations: Experience with backup and recovery, point-in-time recovery, replication, high availability, failover, capacity planning, storage management, monitoring and routine maintenance.
• Security and compliance: Strong understanding of roles, privileges, authentication, encryption, auditing, data protection and database security standards.


Database Design, Data Modelling and Analysis
• Database design: Ability to translate functional and non-functional requirements into scalable, secure and maintainable relational database designs.
• Data modelling: Strong experience creating conceptual, logical and physical data models, entity-relationship diagrams, schemas, tables, keys, constraints and data dictionaries.
• Normalisation: Sound knowledge of normalisation and denormalisation techniques, referential integrity, data quality controls and appropriate modelling patterns.
• Data analysis: Ability to profile and analyse datasets, identify relationships and anomalies, validate data quality, reconcile results and support root-cause analysis.
• Documentation: Experience maintaining database standards, design specifications, lineage, metadata and operational runbooks.


ETL and Data Integration
• ETL development: Hands-on experience designing, developing, scheduling and supporting ETL workflows for extracting, transforming and loading data across heterogeneous sources and targets.
• Data transformation: Strong knowledge of data mapping, cleansing, validation, deduplication, reconciliation, error handling and restart/recovery processes.
• Performance and reliability: Ability to optimise batch loads, manage large data volumes, implement incremental and change-data-capture patterns, and monitor pipeline performance.
• Production support: Experience troubleshooting database and ETL failures, conducting root-cause analysis, implementing permanent fixes and supporting controlled releases.
• Collaboration: Ability to work effectively with applica tion, data engineering, architecture, infrastructure and business teams to deliver reliable data solutions.
• Administer, configure, patch, upgrade and maintain PostgreSQL databases across development, test and production environments.
• Design and implement scalable relational database structures, including schemas, tables, keys, constraints, indexes and data dictionaries.
• Develop, review and optimise complex SQL queries, views, stored procedures, functions and triggers for transactional and reporting requirements.
• Monitor database health and performance; analyse execution plans and resolve query bottlenecks, locking, blocking and long-running transactions.
• Manage backup, restore, point-in-time recovery, replication, high availability and failover processes, and regularly validate recoverability.
• Perform capacity planning, storage management, routine maintenance and proactive monitoring to ensure database availability, scalability and reliability.
• Create and maintain conceptual, logical and physical data models; apply normalisation, denormalisation and referential-integrity standards.
• Profile and analyse data, identify anomalies, validate data quality, reconcile results and support root-cause analysis.
• Design, develop, schedule and support ETL workflows, including data mapping, cleansing, transformation, validation, deduplication and error handling.
• Optimise batch and large-volume data loads, and implement incremental-load and change-data-capture patterns where required.
• Implement and maintain database security controls covering roles, privileges, authentication, encryption, auditing and data protection.
• Troubleshoot database and ETL incidents, implement permanent fixes, support controlled releases and maintain operational runbooks, metadata and data-lineage documentation.
• Collaborate with application, data engineering, architecture, infrastructure, QA and business teams to deliver secure and reliable data solutions.

Salary Range: $90,000 to $130,000 per year